How Close Is Kimi K3.1 Pro To The Frontier? Three Points

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Moonshot AI’s Kimi K3.1 Pro scored 55.1 on Artificial Analysis’s Intelligence Index, ranking fourth in figures published as of October 24 and trailing the highest score, Claude Opus 5.5’s 57.6, by 2.5 points. The model is available through Kimi apps, Kimi Work, Kimi Code and the Kimi API, but Moonshot has only promised to publish its weights by November 4, and has not published a licence for this version.

Artificial Analysis’s launch-day evaluation places K3.1 Pro behind Claude Opus 5.5 at 57.6, Claude Sonnet 5.5 at 56.0 and Muse Wonder Full at 55.8. The score is a marked improvement over the previous Kimi K3, which recorded 43.6 in the same comparison. Artificial Analysis says K3.1 Pro would lead open-weight models if its weights are published; that status is conditional, not current.

The strongest reported gain is on agentic coding work. K3.1 Pro scored 67% on Terminal-Bench 4.0 in Artificial Analysis’s evaluation, compared with 13% for Kimi K3. The company also reports 1,846 Elo on GDPval-AA, a simulated knowledge-work test, behind Opus 5.5 at 1,866 and Muse Wonder Full at 1,857. On Humanity’s Last Exam, K3.1 Pro scored 52%, below Opus 5.5’s 61%.

Artificial Analysis lists the model as a mixture-of-experts system with 2.8 trillion total parameters and 104 billion active parameters, a one-million-token context window and text and image input. Its listed API rates are $2 per million input tokens and $10 per million output tokens. Artificial Analysis estimates $2.11 per Intelligence Index task, compared with $5.98 for Opus 5.5 at the settings used in its table.

A Narrower Gap for Open Weights

The score matters because it places K3.1 Pro near leading proprietary systems on a broad benchmark, while the model is presented as a candidate for an open-weight release. If the weights are published on schedule under a usable licence, developers and organisations could have more control over where the model runs and how it is integrated than they do with a hosted-only service. Those benefits are not available from the benchmark score alone: the promised release and its terms remain outstanding.

Price is another point of interest for teams comparing hosted APIs. Artificial Analysis estimates $2.11 per index task for K3.1 Pro against $5.98 for Opus 5.5, using its own task-cost methodology and the prices and reasoning settings shown in its comparison. That does not establish that K3.1 Pro is cheaper for every workload or delivers equivalent results in every application. The model’s weaker score on some tests, deployment costs and task-specific performance all affect real-world value.

The large improvement on Terminal-Bench suggests a particular strength in tool use and multi-step coding tasks, but one benchmark is not proof of broad reliability. Companies considering the model will need to test it against their own tasks, data-handling requirements and failure costs, rather than treating an overall index ranking as a guarantee.

What the Benchmarks Measure

Kimi K3.1 Pro is described by Moonshot as a more heavily post-trained version of Kimi K3. Artificial Analysis evaluated it at its highest reasoning setting and compared it with other models using the figures available on October 24. Its Intelligence Index combines multiple evaluations; the score is not a direct measure of performance on every user’s workload. Rankings can also change as providers update models or evaluators add results.

Moonshot’s launch material includes additional claims about creating projects in Unity, Unreal Engine and Godot, producing parametric 3D models, and improving finance-related work. These examples and many of the supporting results are vendor demonstrations or internal tests, not independent confirmation of general capability. For example, Moonshot says its internal Kimi Hallu Bench Hard test found claim-level hallucinations fell from 23.4% for Kimi K3 to 8.3% for K3.1 Pro. Artificial Analysis measured a smaller change on its separate AA-Omniscience evaluation, from 53% to 44%. The tests use different methods, so their results should not be treated as directly interchangeable.

Artificial Analysis lists K3.1 Pro at $2 per million input tokens and $10 per million output tokens. Its comparison puts the previous open-weights leaders, including Xiaomi’s MiMo-V2.6-Pro at 46.3, below K3.1 Pro’s 55.1. However, K3.1 Pro is not yet downloadable as open weights. Its listed status is “promised by Nov 4”, not released.

“The Kimi Hallu Bench Hard test is “deliberately crafted” to provoke errors, and the rates “do not represent overall error rates in daily use.””

— Moonshot AI

Weights, Licensing and Real-World Results

The key unresolved issue is whether Moonshot will publish K3.1 Pro’s weights by November 4, and under what licence. No K3.1 licence had been published in the source material, so users cannot yet confirm the permissions or restrictions that would govern downloading, modifying or redistributing the model. A model with 2.8 trillion total parameters may also require substantial infrastructure to run locally; open weights would not, by themselves, make deployment practical for every user.

It is also unclear how well the benchmark results will transfer to production work. Artificial Analysis’s tests offer an external comparison, but they do not establish reliability across all coding, research or business tasks. Moonshot’s game-development, CAD and finance examples remain company claims, and the internal hallucination figure is not a general-use error rate. Independent evaluation of those specific demonstrations and results has not been provided here.

The November Release Test

The next concrete milestone is Moonshot’s promised November 4 weight release. When it arrives, users and evaluators can check whether the published model matches the version assessed, review the licence, and test performance outside Moonshot’s hosted services. Until then, K3.1 Pro is accessible through Moonshot’s apps, products and API rather than as a publicly downloadable weight set.

Further independent testing will help establish whether its agentic coding lead persists across other evaluations and whether its benchmark advantage translates into dependable, cost-effective work. For now, the confirmed picture is a strong fourth-place index result, a notable Terminal-Bench score and a release plan whose timing and terms have yet to be verified.

Key Questions

How close is Kimi K3.1 Pro to the top model?

Artificial Analysis scored it at 55.1, compared with 57.6 for Claude Opus 5.5 in the figures available October 24. That is a 2.5-point difference on the index, where K3.1 Pro ranked fourth.

Is Kimi K3.1 Pro open weight now?

No. Moonshot has promised to publish the weights by November 4, 2026, but they were not available in the source material. No licence for K3.1 had been published either.

What does K3.1 Pro cost through the API?

Artificial Analysis lists prices of $2 per million input tokens and $10 per million output tokens. Its estimated cost per Intelligence Index task is $2.11, based on its comparison methodology.

Are the hallucination claims independently verified?

Moonshot’s reported 65% reduction comes from its internal Kimi Hallu Bench Hard test, which the company says is deliberately designed to provoke errors and does not reflect overall daily-use error rates. Artificial Analysis recorded a fall from 53% to 44% on its separate AA-Omniscience test.

Source: ThorstenMeyerAI.com